def _validate_nlu(self, training_data: TrainingData) -> None:
"""Validates whether the configuration matches the training data.
Args:
training_data: The training data for the NLU components.
"""
training_data.validate()
self._raise_if_more_than_one_tokenizer()
self._raise_if_featurizers_are_not_compatible()
self._warn_of_competing_extractors()
self._warn_of_competition_with_regex_extractor(training_data=training_data)
self._warn_if_some_training_data_is_unused(training_data=training_data)
def test_validate_number_of_examples_per_intent():
message_intent = Message(data={
"text": "I would like the newsletter",
"intent": "subscribe"
})
message_non_nlu_intent = Message(data={"intent": "subscribe"})
training_examples = [message_intent, message_non_nlu_intent]
training_data = TrainingData(training_examples=training_examples)
with pytest.warns(Warning) as w:
training_data.validate()
assert len(w) == 1
assert (w[0].message.args[0] ==
"Intent 'subscribe' has only 1 training examples! "
"Minimum is 2, training may fail.")